IEEE

CMHLFG: A Cross-layer Multihop Graph Convolution and High-Low-Frequency Graph Attention Fusion Network for Hyperspectral Image Classification

Abstract: Graph convolutional networks (GCNs) have emerged as a prominent research focus for hyperspectral image classification (HSIC). However, existing GCN-based HSIC methods still face the ...
Frontiers

CausalX-Net: a causality-guided explainable segmentation network for brain tumors

Brain tumors represent a significant health challenge in India, with approximately 28,000 new cases diagnosed annually. Conventional deep learning approaches for MRI-based segmentation often struggle ...
Frontiers

Correction: Short-time photovoltaic output prediction method based on depthwise separable convolution Visual Geometry group- deep gate recurrent neural network

Clevert, D.-A., Untertiner, T., and Hochreiter, S. (2016). Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). arXiv [Preprint]. Available ...
IEEE

SRS: Siamese Reconstruction-Segmentation Network Based on Dynamic-Parameter Convolution

Abstract: Dynamic convolution demonstrates outstanding representation capabilities, which are crucial for natural image segmentation. However, it fails when applied to medical image segmentation (MIS) ...